Abstract: In order to deal with the relatively high timccomplexity of practical issuc,parallel modern optimization based on GPU was presented in this paper. Firstly, CUDA parallel programming architecture and programming model were summarized at a macroscopic level. Then the parallel processes of five typical modern optimization algorithms(Simulated Annealing, Tabu Search, Genetic Algorithms, Particle Swarm Optimization and Artificial Neural Network) using CUDA programming model were provided. Experimental statistics measured in different environment indicate that the parallel method can obtain better performance on average than CPU. Finally the parallel optimization strategy was discussed and the outlook of future direction of parallel optimization algorithm was also pointed out.

Key words: Modern optimization algorithms, GPU, CUDA, Combinatorial optimization, Parallel computing